5G edge cloud network design

ABSTRACT

Systems and methods may use a math programming model for designing an edge cloud network. The edge cloud network design may depend on various factors, including the number of edge cloud nodes, edge cloud node location, or traffic coverage, among other things.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of, and claims priority to, U.S.patent application Ser. No. 15/950,360, filed Apr. 11, 2018, entitled 5GEDGE CLOUD NETWORK DESIGN,” the entire contents of which are herebyincorporated herein by reference.

TECHNICAL FIELD

The technical field generally relates to edge cloud nodes and, morespecifically, to systems and methods for managing edge cloud nodes.

BACKGROUND

Telecommunication carriers are faced with an explosive growth in mobiletraffic, as all varieties of applications are communicating overcellular networks. To meet the increasing demand, large amounts of newinfrastructure will be needed, which leads to huge capital expenses andoperational costs. The new technology may be utilized to expand thecapacity of the networks, while keeping expenses relatively low.

SUMMARY

An advance in 5G wireless technology is that it enables thevirtualization of the Radio Access Networks (vRAN). In such a design,some functions of the base station (BS) may be moved to a sharedinfrastructure edge cloud (EC) node. This results in less equipmentrequirements at the BS location. It also enables sharing networkresources such as compute and storage, which can result in significantimprovements in key network performance indicators, such as spectralefficiency and energy efficiency. Disclosed herein are systems andmethods for building an EC network that may reduce the networkinvestment expenses and improve network performance.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter. Furthermore,the claimed subject matter is not limited to limitations that solve anyor all disadvantages noted in any part of this disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

Reference will now be made to the accompanying drawings, which are notnecessarily drawn to scale.

FIG. 1 illustrates an exemplary system that may implement edge cloudnetwork design system as disclosed herein.

FIG. 2 illustrates an exemplary method for implementing edge cloudnetwork design.

FIG. 3 illustrates an exemplary method for implementing edge cloudnetwork design.

FIG. 4 illustrates an exemplary system that used various inputs toselect particular edge cloud nodes.

FIG. 5A illustrates an exemplary edge cloud network design based on afirst traffic coverage.

FIG. 5B illustrates an exemplary edge cloud network design based on asecond traffic coverage.

FIG. 6 illustrates a schematic of an exemplary network device.

FIG. 7 illustrates an exemplary communication system that provideswireless telecommunication services over wireless communicationnetworks.

FIG. 8 illustrates an exemplary telecommunications system in which thedisclosed methods and processes may be implemented.

DETAILED DESCRIPTION

Radio access networks (RAN) account for a majority (e.g., 70%˜80%) ofwireless network expenses. In the current RAN design, base stations (BS)have been dimensioned to handle the local busy-hour traffic. Not only isthis design inefficient in terms of resource utilization, but thesituation is worsened by the traffic mobility in the network. One of themain advances in 5G wireless technology is that it enables thevirtualization of the RAN (vRAN). In such a design, some functions ofthe BS may be moved to a shared infrastructure EC node. This results inless equipment requirements at the BS location. It also enables sharingnetwork resources such as compute and storage, which can result insignificant improvements in key network performance indicators, such asspectral efficiency and energy efficiency. Building an EC network mayreduce the network investment expenses and improve network performance.

The EC network design is dependent on the underlying transport networktopology. Typically, a BS is connected to a nearby wire center (WC) or acentral office (CO) at the edge of the network via a direct fiber link.The CO and other network nodes are interconnected via a fiber transportnetwork. A subset of COs and other network nodes are designated ascandidate EC nodes (CEC). If a CEC node is chosen to be an EC node, thencompute, storage, and networking capacity should be built at that nodelocation.

In a 5G network, the traffic/signal at the BS is sent to an EC,processed there and sent back to the BS, all via the transport network.The servers at the ECs and the network itself have limited capacity,which needs to be factored into the network design. In order to maintainreliability/resiliency of the network, a BS should be connected tomultiple EC's within the latency limits. This will ensure that, if oneEC fails (or is down for maintenance) there is another available toserve the traffic. The EC network should cover a specific portion of thetraffic determined by strategic or financial motivations.

The disclosed EC network design may minimize the EC network costs, whichdepend on various factors, including (1) the number of EC nodes, (2) ECnode location, (3) investment cost, (4) operation cost, or (5) the BS toEC assignment, among other things. These are determined such thatbusiness, engineering, and performance requirements are satisfied.Constraints may include ensuring the following: (1) a certain portion oftraffic is covered (coverage constraint); (2) the EC capacities (e.g.,computing, storage) are not exceeded (capacity constraint); (3) thetransport link capacity (how many traffic can flow through eachtransport link); (4) to address traffic with different latencyclassification (e.g., at same BS, traffic for remote surgery and trafficfor regular phone conversation may have very different latencyrequirements and should be treated differently (traffic splicing)); (5)the latency from a BS to the assigned EC through a transport route iswithin the latency requirement (latency constraint); (6) there isconnectivity to multiple ECs with latencies within specified, possiblydifferent, limits; or (7) a specific level of reliability is achievedthrough redundancy (reliability constraint).

FIG. 1 illustrates an exemplary system that may implement edge cloudnetwork design system as disclosed herein. System 100 includes multiplenodes, such as candidate node 101—candidate node 108. Each candidatenode may be a building or the like that a service provider (e.g., mobilephone telecommunications provider) may have network equipment to providenetwork functions. Network equipment may include servers, storagedevices, or the like and network functions may be functions that areused to provide a service for mobile devices (e.g., mobile phone 121,autonomous vehicle 122, or other user equipment). System 100, inaddition, includes wireless base station 110—wireless base station 116.Wireless base station 110 (and the others) may be any one of 5G, LTE,Wi-Fi, or the like base stations. There also may be wire center leafnodes (e.g., WC node 118). In most cases, a base station is connected toa candidate edge cloud node through a wire center. Usually, there is nodirect fiber link between a base station and a candidate edge cloud node(CEC), so when the distance between a base station and a CEC iscalculated, actually the summation of the distance from the base stationto the nearest wire center and the distance between the wire center tothat CEC is calculated.

Server 109, for example, may be used to implement the edge cloud networkdesign system as disclosed herein. Server 109 may receive triggers withregard to the factors herein (e.g., FIG. 3, Table 1 and Table 2). Basedon these triggers (reaching a threshold for the factors), the server mayautomatically suggest an update to the edge cloud network design. Duringdifferent scenarios (e.g., initial implementation, periodic updates,recovery from outages, etc . . . ) determinations may be made withregard to keeping EC network design, as is, or changing the EC networkdesign (e.g., candidate node 108 chosen as an EC node and then is addedto ECs already available or replaces an EC, such as EC node 105 of FIG.4). The edge cloud network design system may also be implemented on anyone or more devices as disclosed herein.

Candidate node 101—candidate node 8, wireless base stations 110—118,mobile device 121—mobile device 122, server 109, and WC node 118 may becommunicatively connected with each other. Candidate node 101—candidatenode 108, among other similar candidate nodes as shown, may be known ascandidate edge cloud (CEC) nodes. Discussed in more detail herein aremethods and systems for determining which candidate nodes should becomeedge cloud nodes. As shown in system 100, candidate nodes (e.g.,candidate node 106) may be connected to base stations through one hop(e.g., no intermediary node), such as link 125 that connects wirelessbase station 115 and candidate node 106 or through multiple hops (e.g.,intermediary nodes), such as wireless base station 114 connecting withcandidate node 106 through link 126 and link 127 with intermediarycandidate node 127. FIG. 2 illustrates an exemplary method forimplementing edge cloud network design system in view of FIG. 3. At step131, first information may be obtained. The first information mayinclude traffic demand forecast 141 (e.g., 5G traffic demand forecast),transport network geographic data 142, network topology data 143 (e.g.,fiber network topology), site morphology data 144, cost data 145,shortest BS-WC path data 146, and shortest CO path data 147, among otherthings. This first information of step 131 may be processed and placedwithin a database 151, which is disclosed in more detail herein. At step132, second information may be obtained. The second information may beconsidered scenario setting information 152, such as latencyrequirements 148 (e.g. minimum latency over a period between a UE and aEC node), reliability requirements 149, and edge cloud server capacity(e.g., minimum processing capacity of a server, node, or deviceimplementing a particular needed service). The scenario settings may bedirectly processed using database 151 or sent to math programming model153. At step 133, based on the first information via the database andthe second information, determining edge cloud (EC) network designinformation 154. The EC network design information 152 may includenumber of EC nodes needed, location of the EC nodes, or base station toEC assignment, among other things.

Discussed below in more detail are exemplary inputs and outputsassociated with implementing an edge cloud network design system (SeeFIG. 3). Demand forecast 141 may be, for example, a traffic forecast atthe base station level. The demand forecast may determined based oninformation comprising historical data, types of traffic, such as audio,video, voice, global positioning system data, autonomous car relateddata (e.g., data historically associated with autonomous vehicles-typeapplications), mobile phone related data, or other UE related data,among other things. Historical traffic data may be based on differentperiods of weeks, months, or 2 or 3 years. Traffic data may be estimatedalso based on census information and projections.

With continued reference to FIG. 3, transport network geographic data142 may include location of base stations (also disclosed as wirelessbase station), morphology of base stations, or location of candidatenodes (e.g., central offices), among other things.

Network topology data 143 may include list of nodes, interconnectinglinks, latency, routing costs, or routing protocols. For example, it mayinclude fiber, nodes, links, or IP network defined on the fiber network,among other things.

Cost data 145 may include EC capital (for different EC options) ortransport cost of -candidate node routes. EC capital cost may includeconstruction cost, hardening against floods, hurricanes and externalfires cost for power, cooling and inside fire suppressant systems,transport connectivity, equipment or hardware cost. These costs may beproportional to traffic, compute, or storage capacity that may beaccommodated at the site. EC options may include a small number ofchoices of standard EC's sizes. For example, a large EC may include 1000or more computer servers, and a medium EC may include 500 up to 999servers, etc. Once the model determines building an edge cloud at alocation, it may be used to further choose to build a large, medium, orsmall EC at that location by iterating on the capacity made available atthe location. Transport costs of a route may depend on cost of right ofway, fiber, optical, or routing equipment needed at each component ofthe route.

With continued reference to FIG. 3, a scenario setting input (e.g.,second information) may include latency requirements 148, such as basedon a function split option. Functional split decision factors mayinclude cost and efforts, operator optimization target, backhaul and RANconstraints, and centralization gains. When considering latency, theremay be a determination that certain UEs will need certain consistentthreshold roundtrip times. For example, if an area consistently usesautonomous vehicles, which has a 3 ms roundtrip requirement, then thatwill be considered. Another input may include reliability requirements149, number of redundant EC nodes required to meet the reliabilityrequirement. Herein, there is usually at least two EC nodes required foreach base station. Input may also include percent of traffic required tobe covered (e.g., meet latency and reliability requirements).

First Information: With continued reference to FIG. 3, data that may bederived from other data disclosed herein and used as input into database151, which may include all data with certain format and are requested bythe math programming model. Pre-calculated shortest BS-WC path data 146(e.g., shortest path between base station (BS) and WC), shortest CECpath data 147 (e.g., shortest route between CECs), nearest CEC to eachBS, set of feasible pairs of BS and a candidate node (also known hereinas candidate EC), or set of routers where the transport link K isincluded, among other things. CEC also may be referred to as a CO. Forthe optimization model, exemplary sets and parameters can be broken downas shown in Table 1 and Table 2.

TABLE 1 Sets Sets BS: Set of BSs CSC: Set of EC candidates K: Set oftransport links COMB: Set of feasible pairs of BS and CEC NBR: Set of ECcandidates within the latency limit for each BS ROU[k]: Set of routeswhich include transport link k

TABLE 2 Parameters Parameters T: Traffic at BS Cost_(EC): Cost per EC,construct expenses and EC operation cost Cost per route, operation costfor using transport links Latency, given latency limit at BS Reliabilityrequirements, N (# of redundant ECs required for reliabilityrequirement) % of traffic required to be covered (i.e., meet latency andreliability requirements) Route Length for each route in COMB CAP,Capacity at EC CAP_LINK, Capacity at transport link

Disclosed below is an exemplary math programming model that may be used.It is contemplated that the below may be altered to fit network designsand other considerations. Below are decision variables. Define a binaryvariable Y for each EC candidate that takes a value of 1 if the CEC ischosen as an EC, and 0 otherwise

${\forall{l \in {CEC}}},{{Y\lbrack l\rbrack} = \left\{ \begin{matrix}{1,} & {{{if}\mspace{14mu}{build}\mspace{14mu}{EC}\mspace{14mu}{at}\mspace{14mu}{location}\mspace{14mu} l};} \\{0,} & {{Otherwise};}\end{matrix} \right.}$

Define a binary variable X for each possible pair of BS and CEC, whichtakes value 1 if the BS is assigned to a CEC which has been chosen as anEC, 0 otherwise.

${\forall{\left( {i,l} \right) \in {COMB}}},{{X\left\lbrack {i,l} \right\rbrack} = \left\{ \begin{matrix}{1,} & {{{if}\mspace{14mu}{BS}\mspace{14mu} i\mspace{14mu}{connect}\mspace{14mu}{to}\mspace{14mu}{ECl}};} \\{0,} & {{Otherwise};}\end{matrix} \right.}$

Below is placement and assignment constraint. A BS can be assigned to anEC location if an EC will be built at that location ∀l∈CEC, M is a bignumberΣ_((i,l)∈COMB) X[i,l]≤M*Y[l]

Below is an objective function which assist in minimizing cost.

${Min}\left( {{\sum\limits_{l \in {CEC}}{Cos{t_{EC}\lbrack l\rbrack}*{Y\lbrack l\rbrack}}} + {\sum\limits_{{({i,l,})} \in {COMB}}{Cos{t_{route}\left\lbrack {i,l} \right\rbrack}*{X\left\lbrack {i,l} \right\rbrack}}}} \right)$

Below is an assignment constraint. A BS can be assigned to at most oneEC. ∀i∈BS,Σ_((i,l)∈COMB) X[i,l]≤1

Below is EC capacity constraints. Aggregated traffic T[i] at EC node≤ECcapacity (for compute, storage, networking).Σ_(i∈BS)Σ_((i,l)∈COMB) X[i,l]*T[i]≤CAP[l],

Below is a traffic coverage constraint. Covered traffic by all ECs mustbe larger or equal to a give percentage of total traffic:Σ_(i∈BS)Σ_((i,l)∈COMB) X[i,l]*T[i]≥% of Total_Traffic,

Below is a resiliency constraint. At least N EC nodes must be builtwithin latency limits for each BS, ∀i∈BS,

${\sum\limits_{\underset{{({i,l})} \in {COMB}}{l \in {{NBR}{\lbrack i\rbrack}}}}{Y\lbrack l\rbrack}} \geq N$

Below is a latency constraint. The length of the primary route≤latencylimit, ∀i∈BS, ∀(i,l)∈COMBX[i,l]*route_length[i,l]≤Latency_limit[i]

Below is a transport link capacity constraint. All traffic which flowthrough transport link k must respect the link capacity

${{\forall{k \in K}}{\sum\limits_{{({i,l})} \in {RO{U{\lbrack k\rbrack}}}}{{X\left\lbrack {i,l} \right\rbrack}*{T\lbrack i\rbrack}}}} \leq {{CAP\_ LINK}\lbrack k\rbrack}$

Below is consideration of traffic splicing. The Traffic at a BS can bedivided according to different latency requirements. The trafficnotation T[i] actually should be T[i,j], which is the traffic at BS iwith latency limit classified as j. By the same token, X[i,l] should beX[i,j,l] which is a binary variable, takes value 1 when traffic at BS i,classified as j will be sent to EC l, otherwise 0. Notation for allrelated parameters, variables, constraints should be modifiedaccordingly. While the format is kept the same, the notation withtraffic classification will become more complicated. For simplicityreason, and without losing generality, we still use current notations.

After consideration of the input through the different data and mathprogramming models there may be various different outputs. The outputs,again which may be based on the inputs disclosed herein (e.g.,associated FIG. 2 and FIG. 3), may be number of EC nodes, location of ECnodes, BS to EC node assignment, investment expenses (e.g., upfrontequipment costs), or operation cost (e.g., ongoing cost, such as powerand maintenance), among other things. FIG. 4 illustrates an exemplarydisplay of an output after running the considerations in associationwith FIG. 1 through the network design system disclosed herein. As shownin FIG. 4, there are six EC nodes that meet the desired requirements andother considerations. There may have been a round trip latency limit of5 ms and a redundancy requirement of two connections to EC nodes withinthe latency limit, among other things. As disclosed herein, input thatmay have been considered (e.g., inputted) into the model may have beenthe number of candidate nodes, the number of base stations, the numberof wired centers, or percent of traffic coverage, among other things.FIG. 5A and FIG. 5B show the impact of traffic coverage on edge clouddesign. FIG. 5A shows a 74% coverage (e.g., with the factors disclosedherein—FIG. 3, etc . . . ) and FIG. 5B shows an 88% coverage.

Disclosed below are further consideration that provide insight onnetwork design, particularly in the edge cloud context. Cost ReductionOpportunity: RAN Virtualization- RAN virtualization & certain LTE/5G UseCases require EC network solution at the edge. Where to place the ECnodes at the edge to minimize the total cost, while maintaining keyrequirements, such as: Latency, resiliency, capacity, transport networktopology, etc. & realize the benefits.

This is a large scale optimization problem, in which there are a numberof feasible options for how to provide an optimal EC network design. Asimple calculation shows that for a case of 170 EC candidates, if 8 ofthem were chosen as EC nodes (to build how many EC nodes actually shouldbe part of solution, assuming 8 is already known) and ignore the BS toEC assignment (which should be part of solution as well), and assume acomputer can calculate cost and do comparison for 10000 options persecond, it will take 46.4 years to go through all options. Clearlyenumeration is not the way to address this problem.

Disclosed herein is a mathematical programming (MP) approach used tosolve this novel issue. MP can eventually achieve the optimal solutionwithout going through all feasible options. The process to build a MPmodel is to define decision variables, to set up a goal or multiplegoals as the objective function to be optimized over all feasibleoptions, and to use equations and inequalities (constraints) to realizethe placement and assignment logic and to meet business and engineeringrequirements. For example, the specific methodology that may be used isInteger Linear Programming (ILP).

In general, ILP problems is called as NP-hard, which can becomputationally intractable, the key in solving this type of problems isthe scalability of modeling. Another fact is that there are many ways tobuild ILP models to describe a same problem. So the challenges here tosolve this large scale optimization problem are: 1) To build a ILP modelwhich can describe the problem comprehensively; 2) the model must bebuilt in the way such that the number of variables and number ofconstraints needed to describe the problem are as less as possible; and3) to put the knowledge (to the problem) into the data pre-processing tofurther shrink the solution domain.

Most conventional studies in this area assume that the EC nodes havealready been setup (knowing how many EC nodes are needed and where toset up them), and focus on EC capacity option and BS assignment. Thereare multiple differences between conventional studies and the disclosednetwork design system. Most conventional models, for example, do notconsider network reliability (e.g., reliability requirement 149),multiple latency constraints, and traffic splits. The traffic at a basestation may include several types and each with its own latencyrequirement. For example, traffic at a base station may include signalsfrom autonomous cars, which need to be processed and sent back within 3ms, but for signals from a patient monitoring device, which allow 30 mslatency. That is why, as disclosed herein, the traffic may be splitaccording to their types. Some traffic with short latency requirement(e.g., under 6 ms) may send to a nearby edge cloud node, and othertraffic with longer latency requirement (e.g., above 10 ms) may be sentto a central cloud node. With this flexibility, we may be able to designa minimum cost EC network with multiple traffic types. In addition, mostconventional models do not consider that a BS may be connected to an ECthrough a route that may consist of several hops and transport links anda latency limit applied to the route.

The disclosed network design system may need much less EC nodes thanconventional approaches for the same traffic coverage requirement. Theplacement of new EC sites may help satisfy the increased demandsrequired by emerging technologies, such as tactile Internet, smart cars,Internet of Things (IoT), sensor networks, smart homes, etc. Thedisclosed method may be applied to these emerging technologies,resulting in addressing the unique latency and reliability requirementsfor implementations connected with the cloud. The disclosed system todetermine the placement of these EC nodes, includes various uniqueconstraints or cost objectives. The system may use mathematicalprogramming/optimization or heuristic methods, and is scalable tothousands of EC locations. The network design system may be used as areal-time selector of EC nodes, a software network simulator for 5Gnetwork scenario analysis, financial and marketing analysis, andoperational planning. The network design system may be used to providecase studies such as: 1) comparing different latency limits vs differentnetwork investment expenses; and 2) tradeoffs between investmentexpenses and network coverage. The disclosed network design system maybe used to create a framework for cloud network designs. If a CEC nodeis chosen to be an EC node, then compute, storage, and networkingcapacity should be built at that node location. Building here may alsomay be remotely turning on compute, storage, and networking capacity.For example, automatically turning on shutdown devices or interfaces,the creation of a virtual machine to provide the service, or the like.

Below provides additional perspective on EC network and the disclosed ECnetwork design. What is an EC network and why it is needed? Traffic aresignals sent to the network by UEs which may be through wirelesscommunication. For example, a UE (e.g., autonomous car) may getsatellite signals for positioning purpose, which cannot be processed bythe UE itself, unless the UE installs expensive components. So, UEs sendthese signals to the network nodes (currently BSs) and then the networkwill send the processed data (positioning data) back to UEs. To do so,computing capacity and storage capacity must be installed at BSs suchthat BSs can process these signals. Since multiple (hundreds andthousands) UEs may share the capacity at a BS, it is a saving approach.To install computing capacity and storage capacity at each BS (e.g., aprovider may have over 50000 BS) is still expensive. In future networks(e.g., 5G), and EC network may be built, in which the traffic (e.g.,signals) of UEs are further sent to EC nodes through BSs, and areprocessed there. Instead of installing expensive computing and storagecapacity at BSs, we now only install them at ECs, and one EC may beshared by multiple BSs (actually, one EC may handle traffic fromhundreds of BSs). This EC network design may further reduce costs for aservice provider.

Where can we build Edge Cloud nodes (e.g., determine candidate nodes)? Aservice provider may already own the sites. .A service provider mayconsider whether there is enough space to install equipment, and thesites should be inter-connected with the service provider's network(BSs, other sites, etc.) by links (e.g., fiber links). Generally, thendefine these locations as the candidates of EC nodes (CECs). In anexample, metro area there may be 2000 base stations, and 200 (qualified)CECs, in which (for example purposes) there may be 10 EC nodes that maycover 88 percent of traffic with each BS connected to two redundant ECnodes.

Again, as disclosed herein, EC network design may be based on severalconsiderations, such as capacity, latency, reliability, or trafficcoverage, among others. Capacity Consideration: the computing capacity(e.g., CPUs—processing power total, per device, per device catering to aparticular service) and storage capacity (e.g., GBs) at an EC arelimited and one EC may only handle the traffic sent from certain numberof BSs.

Latency consideration: Since the signals of UEs will be sent to ECsthrough BSs, and processed data will be sent back to UEs, a firmrequirement for the round-trip transport time may be calculated orotherwise obtained. Historical latency figures, current ping (or liketests), or distance calculations may be used to determine latency.

Reliability Consideration: To prevent from possible EC failure, it maybe required that every BS must be connected to at least two ECs withinthe latency requirement.

Traffic Coverage requirement: A percentage may be given that requiresbuilding ECs so that a certain portion of all BSs (or traffic) will becovered. A BS is covered may mean there is at least two ECs for each BSand the latency requirement is satisfied (distance is considered).

FIG. 6 is a block diagram of network device 300 that may be connected toor comprise a component of system 100 of FIG. 1 or FIG. 4. Networkdevice 300 may comprise hardware or a combination of hardware andsoftware. The functionality to facilitate telecommunications via atelecommunications network may reside in one or combination of networkdevices 300. Network device 300 depicted in FIG. 6 may represent orperform functionality of an appropriate network device 300, orcombination of network devices 300, such as, for example, a component orvarious components of a cellular broadcast system wireless network, aprocessor, a server, a gateway, a node, a mobile switching center (MSC),a short message service center (SMSC), an automatic location functionserver (ALFS), a gateway mobile location center (GMLC), a radio accessnetwork (RAN), a serving mobile location center (SMLC), or the like, orany appropriate combination thereof. It is emphasized that the blockdiagram depicted in FIG. 6 is exemplary and not intended to imply alimitation to a specific implementation or configuration. Thus, networkdevice 300 may be implemented in a single device or multiple devices(e.g., single server or multiple servers, single gateway or multiplegateways, single controller or multiple controllers). Multiple networkentities may be distributed or centrally located. Multiple networkentities may communicate wirelessly, via hard wire, or any appropriatecombination thereof.

Network device 300 may comprise a processor 302 and a memory 304 coupledto processor 302. Memory 304 may contain executable instructions that,when executed by processor 302, cause processor 302 to effectuateoperations associated with mapping wireless signal strength. As evidentfrom the description herein, network device 300 is not to be construedas software per se.

In addition to processor 302 and memory 304, network device 300 mayinclude an input/output system 306. Processor 302, memory 304, andinput/output system 306 may be coupled together (coupling not shown inFIG. 6) to allow communications between them. Each portion of networkdevice 300 may comprise circuitry for performing functions associatedwith each respective portion. Thus, each portion may comprise hardware,or a combination of hardware and software. Accordingly, each portion ofnetwork device 300 is not to be construed as software per se.Input/output system 306 may be capable of receiving or providinginformation from or to a communications device or other network entitiesconfigured for telecommunications. For example input/output system 306may include a wireless communications (e.g., 3G/4G/GPS) card.Input/output system 306 may be capable of receiving or sending videoinformation, audio information, control information, image information,data, or any combination thereof. Input/output system 306 may be capableof transferring information with network device 300. In variousconfigurations, input/output system 306 may receive or provideinformation via any appropriate means, such as, for example, opticalmeans (e.g., infrared), electromagnetic means (e.g., RF, Wi-Fi,Bluetooth®, ZigBee®), acoustic means (e.g., speaker, microphone,ultrasonic receiver, ultrasonic transmitter), or a combination thereof.In an example configuration, input/output system 306 may comprise aWi-Fi finder, a two-way GPS chipset or equivalent, or the like, or acombination thereof.

Input/output system 306 of network device 300 also may contain acommunication connection 308 that allows network device 300 tocommunicate with other devices, network entities, or the like.Communication connection 308 may comprise communication media.Communication media typically embody computer-readable instructions,data structures, program modules or other data in a modulated datasignal such as a carrier wave or other transport mechanism and includesany information delivery media. By way of example, and not limitation,communication media may include wired media such as a wired network ordirect-wired connection, or wireless media such as acoustic, RF,infrared, or other wireless media. The term computer-readable media asused herein includes both storage media and communication media.Input/output system 306 also may include an input device 310 such askeyboard, mouse, pen, voice input device, or touch input device.Input/output system 306 may also include an output device 312, such as adisplay, speakers, or a printer.

Processor 302 may be capable of performing functions associated withtelecommunications, such as functions for processing broadcast messages,as described herein. For example, processor 302 may be capable of, inconjunction with any other portion of network device 300, determining atype of broadcast message and acting according to the broadcast messagetype or content, as described herein.

Memory 304 of network device 300 may comprise a storage medium having aconcrete, tangible, physical structure. As is known, a signal does nothave a concrete, tangible, physical structure. Memory 304, as well asany computer-readable storage medium described herein, is not to beconstrued as a signal. Memory 304, as well as any computer-readablestorage medium described herein, is not to be construed as a transientsignal. Memory 304, as well as any computer-readable storage mediumdescribed herein, is not to be construed as a propagating signal. Memory304, as well as any computer-readable storage medium described herein,is to be construed as an article of manufacture.

Memory 304 may store any information utilized in conjunction withtelecommunications. Depending upon the exact configuration or type ofprocessor, memory 304 may include a volatile storage 314 (such as sometypes of RAM), a nonvolatile storage 316 (such as ROM, flash memory), ora combination thereof. Memory 304 may include additional storage (e.g.,a removable storage 318 or a non-removable storage 320) including, forexample, tape, flash memory, smart cards, CD-ROM, DVD, or other opticalstorage, magnetic cassettes, magnetic tape, magnetic disk storage orother magnetic storage devices, USB-compatible memory, or any othermedium that can be used to store information and that can be accessed bynetwork device 300. Memory 304 may comprise executable instructionsthat, when executed by processor 302, cause processor 302 to effectuateoperations to map signal strengths in an area of interest.

FIG. 7 depicts an exemplary diagrammatic representation of a machine inthe form of a computer system 500 within which a set of instructions,when executed, may cause the machine to perform any one or more of themethods described above. One or more instances of the machine canoperate, for example, as processor 302, server 109, autonomous vehicle122, mobile phone 121, and other devices of FIG. 1 and FIG. 4. In someembodiments, the machine may be connected (e.g., using a network 502) toother machines. In a networked deployment, the machine may operate inthe capacity of a server or a client user machine in a server-clientuser network environment, or as a peer machine in a peer-to-peer (ordistributed) network environment.

The machine may comprise a server computer, a client user computer, apersonal computer (PC), a tablet, a smart phone, a laptop computer, adesktop computer, a control system, a network router, switch or bridge,or any machine capable of executing a set of instructions (sequential orotherwise) that specify actions to be taken by that machine. It will beunderstood that a communication device of the subject disclosureincludes broadly any electronic device that provides voice, video ordata communication. Further, while a single machine is illustrated, theterm “machine” shall also be taken to include any collection of machinesthat individually or jointly execute a set (or multiple sets) ofinstructions to perform any one or more of the methods discussed herein.

Computer system 500 may include a processor (or controller) 504 (e.g., acentral processing unit (CPU)), a graphics processing unit (GPU, orboth), a main memory 506 and a static memory 508, which communicate witheach other via a bus 510. The computer system 500 may further include adisplay unit 512 (e.g., a liquid crystal display (LCD), a flat panel, ora solid state display). Computer system 500 may include an input device514 (e.g., a keyboard), a cursor control device 516 (e.g., a mouse), adisk drive unit 518, a signal generation device 520 (e.g., a speaker orremote control) and a network interface device 522. In distributedenvironments, the embodiments described in the subject disclosure can beadapted to utilize multiple display units 512 controlled by two or morecomputer systems 500. In this configuration, presentations described bythe subject disclosure may in part be shown in a first of display units512, while the remaining portion is presented in a second of displayunits 512.

The disk drive unit 518 may include a tangible computer-readable storagemedium 524 on which is stored one or more sets of instructions (e.g.,software 526) embodying any one or more of the methods or functionsdescribed herein, including those methods illustrated above.Instructions 526 may also reside, completely or at least partially,within main memory 506, static memory 508, or within processor 504during execution thereof by the computer system 500. Main memory 506 andprocessor 504 also may constitute tangible computer-readable storagemedia.

As shown in FIG. 8, telecommunication system 600 may include wirelesstransmit/receive units (WTRUs) 602, a RAN 604, a core network 606, apublic switched telephone network (PSTN) 608, the Internet 610, or othernetworks 612, though it will be appreciated that the disclosed examplescontemplate any number of WTRUs, base stations, networks, or networkelements. Each WTRU 602 may be any type of device configured to operateor communicate in a wireless environment. For example, a WTRU maycomprise mobile phone 121, autonomous vehicle 122, network device 300,or the like, or any combination thereof. By way of example, WTRUs 602may be configured to transmit or receive wireless signals and mayinclude a UE, a mobile station, a fixed or mobile subscriber unit, apager, a cellular telephone, a PDA, a smartphone, a laptop, a netbook, apersonal computer, a wireless sensor, consumer electronics, or the like.It is understood that the exemplary devices above may overlap in theirfunctionality and the terms are not necessarily mutually exclusive.WTRUs 602 may be configured to transmit or receive wireless signals overan air interface 614.

Telecommunication system 600 may also include one or more base stations616. Each of base stations 616 may be any type of device configured towirelessly interface with at least one of the WTRUs 602 to facilitateaccess to one or more communication networks, such as core network 606,PTSN 608, Internet 610, or other networks 612. By way of example, basestations 616 may be a base transceiver station (BTS), a Node-B, an eNodeB, a Home Node B, a Home eNode B, a site controller, an access point(AP), a wireless router, or the like. While base stations 616 are eachdepicted as a single element, it will be appreciated that base stations616 may include any number of interconnected base stations or networkelements.

RAN 604 may include one or more base stations 616, along with othernetwork elements (not shown), such as a base station controller (BSC), aradio network controller (RNC), or relay nodes. One or more basestations 616 may be configured to transmit or receive wireless signalswithin a particular geographic region, which may be referred to as acell (not shown). The cell may further be divided into cell sectors. Forexample, the cell associated with base station 616 may be divided intothree sectors such that base station 616 may include three transceivers:one for each sector of the cell. In another example, base station 616may employ multiple-input multiple-output (MIMO) technology and,therefore, may utilize multiple transceivers for each sector of thecell.

Base stations 616 may communicate with one or more of WTRUs 602 over airinterface 614, which may be any suitable wireless communication link(e.g., RF, microwave, infrared (IR), ultraviolet (UV), or visiblelight). Air interface 614 may be established using any suitable radioaccess technology (RAT).

More specifically, as noted above, telecommunication system 600 may be amultiple access system and may employ one or more channel accessschemes, such as CDMA, TDMA, FDMA, OFDMA, SC-FDMA, or the like. Forexample, base station 616 in RAN 604 and WTRUs 602 connected to RAN 604may implement a radio technology such as Universal MobileTelecommunications System (UMTS) Terrestrial Radio Access (UTRA) thatmay establish air interface 614 using wideband CDMA (WCDMA). WCDMA mayinclude communication protocols, such as High-Speed Packet Access (HSPA)or Evolved HSPA (HSPA+). HSPA may include High-Speed Downlink PacketAccess (HSDPA) or High-Speed Uplink Packet Access (HSUPA).

As another example base station 616 and WTRUs 602 that are connected toRAN 604 may implement a radio technology such as Evolved UMTSTerrestrial Radio Access (E-UTRA), which may establish air interface 614using LTE or LTE-Advanced (LTE-A).

Optionally base station 616 and WTRUs 602 connected to RAN 604 mayimplement radio technologies such as 5G, IEEE 602.16 (i.e., WorldwideInteroperability for Microwave Access (WiMAX)), CDMA2000, CDMA2000 1X,CDMA2000 EV-DO, Interim Standard 2000 (IS-2000), Interim Standard 95(IS-95), Interim Standard 856 (IS-856), GSM, Enhanced Data rates for GSMEvolution (EDGE), GSM EDGE (GERAN), or the like.

Base station 616 may be a wireless router, Home Node B, Home eNode B, oraccess point, for example, and may utilize any suitable RAT forfacilitating wireless connectivity in a localized area, such as a placeof business, a home, a vehicle, a campus, or the like. For example, basestation 616 and associated WTRUs 602 may implement a radio technologysuch as IEEE 602.11 to establish a wireless local area network (WLAN).As another example, base station 616 and associated WTRUs 602 mayimplement a radio technology such as IEEE 602.15 to establish a wirelesspersonal area network (WPAN). In yet another example, base station 616and associated WTRUs 602 may utilize a cellular-based RAT (e.g., WCDMA,CDMA2000, GSM, LTE, LTE-A, etc.) to establish a picocell or femtocell.As shown in FIG. 8, base station 616 may have a direct connection toInternet 610. Thus, base station 616 may not be required to accessInternet 610 via core network 606.

RAN 604 may be in communication with core network 606, which may be anytype of network configured to provide voice, data, applications, and/orvoice over internet protocol (VoIP) services to one or more WTRUs 602.For example, core network 606 may provide call control, billingservices, mobile location-based services, pre-paid calling, Internetconnectivity, video distribution or high-level security functions, suchas user authentication. Although not shown in FIG. 8, it will beappreciated that RAN 604 or core network 606 may be in direct orindirect communication with other RANs that employ the same RAT as RAN604 or a different RAT. For example, in addition to being connected toRAN 604, which may be utilizing an E-UTRA radio technology, core network606 may also be in communication with another RAN (not shown) employinga GSM radio technology.

Core network 606 may also serve as a gateway for WTRUs 602 to accessPSTN 608, Internet 610, or other networks 612. PSTN 608 may includecircuit-switched telephone networks that provide plain old telephoneservice (POTS). For LTE core networks, core network 606 may use IMS core614 to provide access to PSTN 608. Internet 610 may include a globalsystem of interconnected computer networks or devices that use commoncommunication protocols, such as the transmission control protocol(TCP), user datagram protocol (UDP), or IP in the TCP/IP internetprotocol suite. Other networks 612 may include wired or wirelesscommunications networks owned or operated by other service providers.For example, other networks 612 may include another core networkconnected to one or more RANs, which may employ the same RAT as RAN 604or a different RAT.

Some or all WTRUs 602 in telecommunication system 600 may includemulti-mode capabilities. That is, WTRUs 602 may include multipletransceivers for communicating with different wireless networks overdifferent wireless links. For example, one or more WTRUs 602 may beconfigured to communicate with base station 616, which may employ acellular-based radio technology, and with base station 616, which mayemploy an IEEE 802 radio technology.

As described herein, a telecommunications system wherein management andcontrol utilizing a software designed network (SDN) and a simple IP arebased, at least in part, on user equipment, may provide a wirelessmanagement and control framework that enables common wireless managementand control, such as mobility management, radio resource management,QoS, load balancing, etc., across many wireless technologies, e.g. LTE,Wi-Fi, and future 5G access technologies; decoupling the mobilitycontrol from data planes to let them evolve and scale independently;reducing network state maintained in the network based on user equipmenttypes to reduce network cost and allow massive scale; shortening cycletime and improving network upgradability; flexibility in creatingend-to-end services based on types of user equipment and applications,thus improve customer experience; or improving user equipment powerefficiency and battery life—especially for simple M2M devices—throughenhanced wireless management.

While examples of a telecommunications system in which informationassociated with edge cloud network design may be processed and managedhave been described in connection with various computingdevices/processors, the underlying concepts may be applied to anycomputing device, processor, or system capable of facilitating atelecommunications system. The various techniques described herein maybe implemented in connection with hardware or software or, whereappropriate, with a combination of both. Thus, the methods and devicesmay take the form of program code (i.e., instructions) embodied inconcrete, tangible, storage media having a concrete, tangible, physicalstructure. Examples of tangible storage media include floppy diskettes,CD-ROMs, DVDs, hard drives, or any other tangible machine-readablestorage medium (computer-readable storage medium). Thus, acomputer-readable storage medium is not a signal. A computer-readablestorage medium is not a transient signal. Further, a computer-readablestorage medium is not a propagating signal. A computer-readable storagemedium as described herein is an article of manufacture. When theprogram code is loaded into and executed by a machine, such as acomputer, the machine becomes an device for telecommunications. In thecase of program code execution on programmable computers, the computingdevice will generally include a processor, a storage medium readable bythe processor (including volatile or nonvolatile memory or storageelements), at least one input device, and at least one output device.The program(s) can be implemented in assembly or machine language, ifdesired. The language can be a compiled or interpreted language, and maybe combined with hardware implementations.

The methods and devices associated with a telecommunications system asdescribed herein also may be practiced via communications embodied inthe form of program code that is transmitted over some transmissionmedium, such as over electrical wiring or cabling, through fiber optics,or via any other form of transmission, wherein, when the program code isreceived and loaded into and executed by a machine, such as an EPROM, agate array, a programmable logic device (PLD), a client computer, or thelike, the machine becomes an device for implementing telecommunicationsas described herein. When implemented on a general-purpose processor,the program code combines with the processor to provide a unique devicethat operates to invoke the functionality of a telecommunicationssystem.

While a telecommunications system has been described in connection withthe various examples of the various figures, it is to be understood thatother similar implementations may be used or modifications and additionsmay be made to the described examples of a telecommunications systemwithout deviating therefrom. For example, one skilled in the art willrecognize that a telecommunications system as described in the instantapplication may apply to any environment, whether wired or wireless, andmay be applied to any number of such devices connected via acommunications network and interacting across the network. Therefore, atelecommunications system as described herein should not be limited toany single example, but rather should be construed in breadth and scopein accordance with the appended claims.

In describing preferred methods, systems, or apparatuses of the subjectmatter of the present disclosure—edge cloud network design—asillustrated in the Figures, specific terminology is employed for thesake of clarity. The claimed subject matter, however, is not intended tobe limited to the specific terminology so selected, and it is to beunderstood that each specific element includes all technical equivalentsthat operate in a similar manner to accomplish a similar purpose. Inaddition, the use of the word “or” is generally used inclusively unlessotherwise provided herein. Services as disclosed herein may include IoTservices, such as smart home devices and the services that monitor andrespond to them, on-demand entertainment and streaming services, andmobile phone website and applications related services, among others.And right around the corner are new trends such as virtual reality (VR)and augmented reality (AR) work and infotainment services and autonomoustransports,

This written description uses examples to enable any person skilled inthe art to practice the claimed invention, including making and usingany devices or systems and performing any incorporated methods. Thepatentable scope of the invention is defined by the claims, and mayinclude other examples that occur to those skilled in the art (e.g.,skipping steps, combining steps, or adding steps between exemplarymethods disclosed herein). Such other examples are intended to be withinthe scope of the claims if they have structural elements that do notdiffer from the literal language of the claims, or if they includeequivalent structural elements with insubstantial differences from theliteral languages of the claims.

Methods, systems, and apparatuses, among other things, as describedherein may provide for obtaining first information about atelecommunications network, the first information comprising locationsof a plurality of central offices and distances between the plurality ofcentral offices and a plurality of base stations; obtaining secondinformation, the second information comprising a minimum number of edgecloud nodes that need to be available to connect to each of theplurality of base stations, wherein the minimum number is two; and basedon the first information and the second information, determining an edgecloud network design. There may be an indication of a GPS location of asubset of the plurality of central offices to use as edge cloud nodesbased on the determining of the edge cloud network design. The firstinformation may be processed by a database 151 (e.g., FIG. 3) beforebeing used in the determining of the edge cloud network design. Thefirst information and the second information may be processed by using amath programming model such as provided herein in the determining anedge cloud network design. There may be an indication of a minimumnumber of edge cloud nodes (and the CPU, services, or devices needtherein) based on the determining of the edge cloud network design.There may be an indication (e.g., map, table, etc) of an assignment ofeach of the plurality of base stations to the edge cloud nodes based onthe determining of the edge cloud network design. A display may beupdated or actual devices within the EC node reconfigured for aparticular service to implement an update to a location of a subset ofthe plurality of central offices to use as edge cloud nodes based on thedetermining of the edge cloud network design. The first information mayfurther comprise a traffic coverage for the edge cloud network design,wherein the traffic coverage is based on a traffic forecast based onhistorical paging traffic data, historical tracking area update trafficdata, autonomous vehicle related traffic data, or other historicaltraffic data corresponding to a service. The network device may beserver or user equipment. The network device may send instructions toother devices in the network to obtain the information which may beresult of real-time testing by the other devices. Terminal node (e.g.,base station) process, receive, or send certain amount of traffic, data,computing capacity or storage capacity. Terminal nodes may includewireless base stations which serve a variety of end devices, such asmobile phones, point of sale terminals, devices of data centers, devicesof residences with internet, devices associated with computing andentertainment services, game consoles, Internet of Things (IOT) devices,remote vehicles, or factory equipment, among other things. Anintermediate office (e.g., central office) may include a data transportnetwork of interconnected nodes links and nodes. All combinations inthis paragraph (including the removal or addition of steps) arecontemplated in a manner that is consistent with the other portions ofthe detailed description.

What is claimed:
 1. A system comprising: one or more processors; andmemory coupled with the one or more processors, the memory comprisingexecutable instructions that when executed by the one or more processorscause the one or more processors to effectuate operations comprising:receiving information about a telecommunications network, theinformation comprising: a first latency requirement for a first datatraffic type, wherein the first data traffic type includes data trafficfrom autonomous vehicles; a first redundancy requirement for the firstdata traffic type; routes and latencies between a first edge cloud nodeand a plurality of candidate edge cloud nodes; and respective locationsof the plurality of candidate edge cloud nodes; based on theinformation, assigning a candidate edge cloud node of the plurality ofcandidate edge cloud nodes to be a second edge cloud node of thetelecommunications network; and providing instructions to update an edgecloud network design to indicate the second edge cloud node.
 2. Thesystem of claim 1, the operations further comprise providing anindication of a location of a subset of a plurality of intermediateoffices to use for edge cloud nodes based on the update of the edgecloud network design.
 3. The system of claim 1, wherein the informationis processed using a math programming model for determining the edgecloud network design.
 4. The system of claim 1, the operations furthercomprise providing an indication of a minimum number of edge cloud nodesbased on the update of the edge cloud network design.
 5. The system ofclaim 1, the operations further comprise providing an indication of anassignment of each of a plurality of terminal nodes to edge cloud nodesbased on the update of the edge cloud network design.
 6. The system ofclaim 1, the operations further comprise providing instructions toupdate a location of a subset of a plurality of intermediate offices touse for edge cloud nodes based on the update of the edge cloud networkdesign.
 7. The system of claim 1, wherein the information furthercomprises a traffic coverage for the edge cloud network design, whereinthe traffic coverage is based on a traffic forecast.
 8. The system ofclaim 1, wherein the information further comprises a traffic coveragefor the edge cloud network design, wherein the traffic coverage is basedon a traffic forecast, wherein the traffic forecast is based onhistorical paging traffic data.
 9. The system of claim 1, wherein theinformation further comprises a traffic coverage for the edge cloudnetwork design, wherein the traffic coverage is based on a trafficforecast, wherein the traffic forecast is based on historical trackingarea update traffic data.
 10. The system of claim 1, wherein theinformation further comprises a traffic coverage for the edge cloudnetwork design, wherein the traffic coverage is based on a trafficforecast, wherein the traffic forecast is based on autonomous vehiclerelated traffic data.
 11. The system of claim 1, wherein the informationfurther comprises a minimum latency between a plurality of intermediateoffices and a user equipment.
 12. The system of claim 1, wherein theinformation further comprises a processing capacity of devices locatedat an intermediate office that implement a service.
 13. A methodcomprising: receiving, by a processor, information about atelecommunications network, the information comprising: a first latencyrequirement for a first data traffic type, wherein the first datatraffic type includes data traffic from autonomous vehicles; a firstredundancy requirement for the first data traffic type; routes andlatencies between a first edge cloud node and a plurality of candidateedge cloud nodes; and respective locations of the plurality of candidateedge cloud nodes; based on the information, assigning, by the processor,a candidate edge cloud node of the plurality of candidate edge cloudnodes to become a second edge cloud node of the telecommunicationsnetwork; and providing, by the processor, instructions to update an edgecloud network design to indicate the second edge cloud node.
 14. Themethod of claim 13, further comprising providing an indication of alocation of a subset of a plurality of intermediate offices to use foredge cloud nodes based on the update of the edge cloud network design.15. The method of claim 13, wherein the information is processed using amath programming model for determining the edge cloud network design.16. The method of claim 13, further comprising providing an indicationof a minimum number of edge cloud nodes based on the update of the edgecloud network design.
 17. A computer readable storage medium storingcomputer executable instructions that when executed by a computingdevice cause said computing device to effectuate operations comprising:receiving information about a telecommunications network, theinformation comprising: a first latency requirement for a first datatraffic type, wherein the first data traffic type includes data trafficfrom autonomous vehicles; a first redundancy requirement for the firstdata traffic type; routes and latencies between a first edge cloud nodeand a plurality of candidate edge cloud nodes; and respective locationsof the plurality of candidate edge cloud nodes; based on theinformation, assigning a candidate edge cloud node of the plurality ofcandidate edge cloud nodes to become a second edge cloud node of thetelecommunications network; and providing instructions to update an edgecloud network design to indicate the second edge cloud node.
 18. Thecomputer readable storage medium of claim 17, wherein the informationfurther comprises a traffic coverage for the edge cloud network design,wherein the traffic coverage is based on a traffic forecast, wherein thetraffic forecast is based on autonomous vehicle related traffic data.19. The computer readable storage medium of claim 17, wherein theinformation further comprises a minimum latency between a plurality ofintermediate offices and a user equipment.
 20. The computer readablestorage medium of claim 17, wherein the information further comprises aprocessing capacity of devices located at an intermediate office thatimplement a service.